Human facial asymmetry has long been a critical factor for evaluations of attractiveness and expressions in psychology and anthropology, although most studies are carried out qualitatively. In this project, we investigate in depth the effect of statistical facial asymmetry measurement as a biometric under expression variations. Our initial findings demonstrate that the asymmetry of specific facial regions captures individual differences that are robust to variation in facial expression. More importantly, our experimental results show that facial asymmetry provides discriminating power orthogonal to conventional face identification methods. The synergy of combining facial asymmetry with conventional methods is evaluated. Our work appears to be the first to show quantitatively the power of facial asymmetry as a biometric. Further studies are carried out on 3D face asymmetry quantifications, pose-invariant human identification, identification rates for attractive v. non-attractive people, gender differences, and temporal variations during expressions for emotion classification.